What is a Data Product?
A data product is a package of data, metadata, characteristics of the data, means of use,
Governance, Quality.
Data Products Spec sheet:
A data product spec sheet will also include the usecases, scenarios and other information..
Data product spec sheet encapsulates the entirety of information that users seek and consume
about the product, including exhaustive details on its sources, technologies employed, use cases,
and generated insights. This encompasses all relevant data-driven insights, aims, and functionalities,
serving as a holistic repository of knowledge vital for understanding the product's utility from a
business perspective. Data product spec sheet details use cases such as: spanning software
applications, platforms, algorithms, or systems, serve to transform raw data into actionable insights,
optimizing processes, enhancing user experiences, and fostering informed decision-making across
diverse industries and domains.
Data Product platform:
It supports ingress data interoperability and egress data interoperability.
Interoperability:
The Customer 360 Data Product demonstrates strong interoperability by seamlessly integrating and
consolidating data from disparate sources, including AWS Redshift, PostgreSQL, and Google Web
Analytics. This interoperability ensures that data from various formats and platforms can be
harmoniously processed and utilized within the system. Additionally, the use of technologies such as
Apache Spark, Apache Kafka, and PostgreSQL databases in the system requirements guarantees that
these components interact efficiently, allowing for smooth data flow and processing across the
entire ecosystem. The architectural diagrams visually represent the interconnections, showcasing the
system's interoperability by illustrating how different components communicate and work together
to create a unified view of customer data.
Reliability:
Reliability in the Customer 360 Data Product is evident through its emphasis on real-time updates
and robust system configurations. The continuous and real-time updates to customer profiles ensure
the accuracy and responsiveness of the system, reflecting its reliability in reflecting current customer
behaviors and preferences. Specifications detailing the Compute Cluster, Apache Kafka Cluster, and
PostgreSQL Database, with specific node configurations and redundancy measures, reinforce the
system's reliability by ensuring high availability and fault tolerance. The architecture's fault-tolerant
design, along with redundancy in clusters, contributes to the system's resilience against failures,
further enhancing reliability.
Governance:
Governance within the Customer 360 Data Product encompasses comprehensive security measures,
compliance considerations, and structured data stewardship. The product incorporates robust
security measures, including encryption for data in transit and at rest, role-based access controls
(RBAC), and stringent audit trails. These measures ensure data integrity, confidentiality, and
regulatory compliance (such as GDPR, HIPAA) while mitigating risks associated with unauthorized